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A comparative investigation of mixing rules for property prediction in Multicomponent electrolyte solutions

Rowland, D. and May, P.M. (2018) A comparative investigation of mixing rules for property prediction in Multicomponent electrolyte solutions. Journal of Solution Chemistry, 47 (1). pp. 107-126.

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A mathematical technique is developed to investigate physicochemical property prediction of solution mixtures from the corresponding properties of the pure dissolved systems, as is often expressed in empirical ‘mixing rules’ such as those of Young and of Zdanovskii. A systematic method to distinguish between the inherent characteristics of such rules is needed because experimental studies have proved indecisive. Sound mixing rules must be found to support current efforts in thermodynamic modelling where conventional approaches like the Pitzer equations lack robustness. Density differences relative to pure water, osmotic coefficients and heat capacities are investigated with mixtures including {NaCl + MgCl2}(aq) and {NaCl + Na2SO4}(aq) as specific examples representing common-anion and common-cation asymmetric strong electrolyte solutions respectively. Water activity curves for hydrochloric acid and the alkali metal chloride solutions are also considered. The results confirm that, at the present state of the art, differences between mixing rules are for the most part insignificant at 25 °C, being about the same or less than would be expected from experimental uncertainty. As the predicted differences are even smaller at higher temperature, it can be posited that all reasonably well-established mixing rules in the literature will give approximately equivalent and satisfactory predictions of solution properties under superambient conditions. This is particularly important since the effects of temperature on the magnitude of ternary interactions are not well known from experiment.

Publication Type: Journal Article
Murdoch Affiliation: School of Engineering and Information Technology
Publisher: Springer Netherlands
Copyright: © 2018 Springer Science+Business Media, LLC, part of Springer Nature
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